基于神经网络的双馈发电机矢量控制

The DFIG Vector Control Based on Neural Network

分析了双馈发电机矢量控制原理,提出了基于神经网络自适应PID控制器对双馈发电机的控制策略。根据扰动的变化,给出相应的输出反馈增益,使得系统能够以满意的阻尼比,无静态误差地跟踪不同的期望工作点,对扰动具有一定的抑制作用。仿真结果表明,该系统具有良好的动态性能。

Variable control theory for doubly-fed induction generator （ DFIG ） is analyzed in this paper, and the control strategy of an adaptive PID controller based on neural network to realize the speed control of DFIG is proposed. According to the change of disturbance variables, the corresponding output feedback gain is obtained, and this makes the system to track different expectation working spot with the satisfied damp ratio and zero static error. Simulation results also show that this system has high dynamic performance.